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A constructing vehicle intrusion detection algorithm based on BOW presentation model

机译:基于BOW表示模型的构造车辆入侵检测算法

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Existed algorithms to detect constructing vehicles intrusion in order to prevent power grid transmission line from damage by using video/image processing can only detect constructing vehicles in a single color. In this paper, a new algorithm to detect invasive constructing vehicles based on BOW presentation model is proposed. Firstly, Gaussian fuzzy operation is imposed on the image and Gaussian mixture modeling method is used to separate the foreground regions from background. Then dense SIFT features are extracted from the foreground regions and the features are quantified by using visual dictionary which have been studied previously. Next, the SVM classifier based on histogram intersection kernel function is applied for vehicle type recognition. Finally, duplicated vehicles are removed and alarming signal is sent to workers who need to deal with the hidden damage actions. The experimental results show that the proposed method can effectively detect large constructing vehicles of different colors and categories.
机译:现有的通过使用视频/图像处理来检测建筑车辆入侵以防止电网传输线损坏的算法只能检测单一颜色的建筑车辆。提出了一种新的基于BOW表示模型的侵入式建筑车辆检测算法。首先,对图像进行高斯模糊运算,并采用高斯混合建模方法将前景区域与背景分离。然后从前景区域提取密集的SIFT特征,并使用先前研究过的视觉词典对特征进行量化。接下来,将基于直方图相交核函数的支持向量机分类器应用于车辆类型识别。最后,将多余的车辆移走,并向需要处理隐患的工人发送警报信号。实验结果表明,该方法能够有效地检测出不同颜色和类别的大型施工车辆。

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